This article introduces hypertables, a feature of TimescaleDB designed to improve query performance on massive volumes of time-series data. Hypertables automatically partition regular PostgreSQL tables into smaller data partitions or chunks, making working with time-series data easier and more efficient. They enable handling high-frequency inserts efficiently, optimizing queries for time-based data, and ensuring fast query performance at scale. The article provides a step-by-step guide on creating hypertables, inserting data, and testing their performance benefits against regular PostgreSQL tables. Hypertables are particularly useful for storing and querying large volumes of time-stamped data in applications such as IoT, weather data, financial data analysis, and system monitoring.